IDEAS home Printed from https://ideas.repec.org/p/ems/eureir/38689.html
   My bibliography  Save this paper

How Volatile is ENSO for Global Greenhouse Gas Emissions and the Global Economy?

Author

Listed:
  • Chu, L-F.
  • McAleer, M.J.
  • Chen, C-C.

Abstract

This paper analyzes two indexes in order to capture the volatility inherent in El Niños Southern Oscillations (ENSO), develops the relationship between the strength of ENSO and greenhouse gas emissions, which increase as the economy grows, with carbon dioxide being the major greenhouse gas, and examines how these gases affect the frequency and strength of El Niño on the global economy. The empirical results show that both the ARMA(1,1)-GARCH(1,1) and ARMA(3,2)-GJR(1,1) models are suitable for modelling ENSO volatility accurately, and that 1998 is a turning point, which indicates that the ENSO strength has increased since 1998. Moreover, the increasing ENSO strength is due to the increase in greenhouse gas emissions. The ENSO strengths for Sea Surface Temperature (SST) are predicted for the year 2030 to increase from 29.62% to 81.5% if global CO2 emissions increase by 40% to 110%, respectively. This indicates that we will be faced with even stronger El Nino or La Nina effects in the future if global greenhouse gas emissions continue to increase unabated.

Suggested Citation

  • Chu, L-F. & McAleer, M.J. & Chen, C-C., 2012. "How Volatile is ENSO for Global Greenhouse Gas Emissions and the Global Economy?," Econometric Institute Research Papers EI 2012-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:38689
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/38689/EI2012-33.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Shiqing Ling & Michael McAleer, 2001. "On Adaptive Estimation in Nonstationary ARMA Models with GARCH Errors," ISER Discussion Paper 0548, Institute of Social and Economic Research, Osaka University.
    2. Divino, J.A. & McAleer, M.J., 2008. "Modelling sustainable international tourism demand to the Brazilian Amazon," Econometric Institute Research Papers EI 2008-22, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. McAleer, Michael & Chan, Felix & Marinova, Dora, 2007. "An econometric analysis of asymmetric volatility: Theory and application to patents," Journal of Econometrics, Elsevier, vol. 139(2), pages 259-284, August.
    4. Bruce E. Hansen, 2001. "The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 117-128, Fall.
    5. Hall, Anthony D. & Skalin, Joakim & Teräsvirta, Timo, 1998. "A nonlinear time series model of El Niño," SSE/EFI Working Paper Series in Economics and Finance 263, Stockholm School of Economics.
    6. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    7. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    8. Allan D. Brunner, 2002. "El Niño and World Primary Commodity Prices: Warm Water or Hot Air?," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 176-183, February.
    9. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    10. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
    11. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    12. Ling, Shiqing & McAleer, Michael, 2002. "Stationarity and the existence of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 109-117, January.
    13. Chen, Chi-Chung & McCarl, Bruce A., 2000. "The Value Of Enso Information To Agriculture: Consideration Of Event Strength And Trade," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(2), pages 1-18, December.
    14. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    15. Nelson, Daniel B., 1990. "Stationarity and Persistence in the GARCH(1,1) Model," Econometric Theory, Cambridge University Press, vol. 6(3), pages 318-334, September.
    16. Ling, Shiqing & McAleer, Michael, 2002. "NECESSARY AND SUFFICIENT MOMENT CONDITIONS FOR THE GARCH(r,s) AND ASYMMETRIC POWER GARCH(r,s) MODELS," Econometric Theory, Cambridge University Press, vol. 18(3), pages 722-729, June.
    17. Berry, Brian J.L. & Okulicz-Kozaryn, Adam, 2008. "Are there ENSO signals in the macroeconomy," Ecological Economics, Elsevier, vol. 64(3), pages 625-633, January.
    18. A. Timmermann & J. Oberhuber & A. Bacher & M. Esch & M. Latif & E. Roeckner, 1999. "Increased El Niño frequency in a climate model forced by future greenhouse warming," Nature, Nature, vol. 398(6729), pages 694-697, April.
    19. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    20. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(1), pages 232-261, February.
    21. Shiqing Ling & W. K. Li, 1997. "Diagnostic checking of nonlinear multivariate time series with multivariate arch errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 18(5), pages 447-464, September.
    22. Carrasco, Marine & Chen, Xiaohong, 2002. "Mixing And Moment Properties Of Various Garch And Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 18(1), pages 17-39, February.
    23. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    24. Guy Debelle & Glenn Stevens, 1995. "Monetary Policy Goals for Inflation in Australia," RBA Research Discussion Papers rdp9503, Reserve Bank of Australia.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Glen Livingston & Darfiana Nur, 2020. "Bayesian inference of smooth transition autoregressive (STAR)(k)–GARCH(l, m) models," Statistical Papers, Springer, vol. 61(6), pages 2449-2482, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chu, L. & McAleer, M.J. & Chen, C-C., 2009. "How Volatile is ENSO?," Econometric Institute Research Papers EI 2009-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Chang, Chia-Lin & Huang, Biing-Wen & Chen, Meng-Gu & McAleer, Michael, 2011. "Modelling the asymmetric volatility in hog prices in Taiwan: The impact of joining the WTO," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1491-1506.
    3. Chang, C-L. & Huang, B-W. & Chen, M-G., 2010. "Modelling the Asymmetric Volatility in Hog Prices in Taiwan," Econometric Institute Research Papers EI 2010-46, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Divino, Jose Angelo & McAleer, Michael, 2010. "Modelling and forecasting daily international mass tourism to Peru," Tourism Management, Elsevier, vol. 31(6), pages 846-854.
    5. Chia-Lin Chang & Michael Mcaleer, 2012. "Aggregation, Heterogeneous Autoregression And Volatility Of Daily International Tourist Arrivals And Exchange Rates," The Japanese Economic Review, Japanese Economic Association, vol. 63(3), pages 397-419, September.
    6. Chia-Lin Chang & Michael McAleer & Christine Lim, 2010. "Modelling the Volatility in Short and Long Haul Japanese Tourist Arrivals to New Zealand and Taiwan," Working Papers in Economics 10/40, University of Canterbury, Department of Economics and Finance.
    7. Chia-Lin Chang & Michael Mcaleer, 2009. "Daily Tourist Arrivals, Exchange Rates and Voatility for Korea and Taiwan," Korean Economic Review, Korean Economic Association, vol. 25, pages 241-267.
    8. Ping-Yu Chen & Chia-Lin Chang & Chi-Chung Chen & Michael McAleer, 2012. "Modelling the Effects of Oil Prices on Global Fertilizer Prices and Volatility," JRFM, MDPI, vol. 5(1), pages 1-37, December.
    9. Ping-Yu Chen & Chia-Lin Chang & Chi-Chung Chen & Michael McAleer, 2010. "Modeling the Effect of Oil Price on Global Fertilizer Prices," Working Papers in Economics 10/55, University of Canterbury, Department of Economics and Finance.
    10. Ping-Yu Chen & Chia-Lin Chang & Chi-Chung Chen & Michael McAleer, 2010. "Modeling the Volatility in Global Fertilizer Prices," Working Papers in Economics 10/46, University of Canterbury, Department of Economics and Finance.
    11. Chia-Lin Chang & Michael McAleer & Christine Lim, 2009. "Modelling Short and Long Haul Volatility in Japanese Tourist Arrivals to New Zealand and Taiwan," CIRJE F-Series CIRJE-F-647, CIRJE, Faculty of Economics, University of Tokyo.
    12. Ana Bartolome & Michael McAleer & Vicente Ramos & Javier Rey-Maquieira, 2009. "Cruising is Risky Business," CIRJE F-Series CIRJE-F-664, CIRJE, Faculty of Economics, University of Tokyo.
    13. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    14. Huang, Biing-Wen & Chen, Meng-Gu & Chang, Chia-Lin & McAleer, Michael, 2009. "Modelling risk in agricultural finance: Application to the poultry industry in Taiwan," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(5), pages 1472-1487.
    15. Chang, Chia-Lin & Jimenez-Martin, Juan-Angel & McAleer, Michael & Amaral, Teodosio Perez, 2013. "The rise and fall of S&P500 variance futures," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 151-167.
    16. Casarin, Roberto & Chang, Chia-Lin & Jimenez-Martin, Juan-Angel & McAleer, Michael & Pérez-Amaral, Teodosio, 2013. "Risk management of risk under the Basel Accord: A Bayesian approach to forecasting Value-at-Risk of VIX futures," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 183-204.
    17. McAleer, M.J. & Jiménez-Martín, J.A. & Pérez-Amaral, T., 2008. "A decision rule to minimize daily capital charges in forecasting value-at-risk," Econometric Institute Research Papers EI 2008-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    18. McAleer, Michael & Jimenez-Martin, Juan-Angel & Perez-Amaral, Teodosio, 2013. "Has the Basel Accord improved risk management during the global financial crisis?," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 250-265.
    19. Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2011. "Risk Management of Risk under the Basel Accord: Forecasting Value-at-Risk of VIX Futures," Working Papers in Economics 11/12, University of Canterbury, Department of Economics and Finance.
    20. Michael McAleer & Juan‐Ángel Jiménez‐Martín & Teodosio Pérez‐Amaral, 2013. "International Evidence on GFC‐Robust Forecasts for Risk Management under the Basel Accord," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(3), pages 267-288, April.

    More about this item

    Keywords

    El Niños Southern Oscillations (ENSO); global Economy; greenhouse gas emissions; sea surface temperature (SST); southern oscillation ndex (SOI); volatility;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ems:eureir:38689. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: RePub (email available below). General contact details of provider: https://edirc.repec.org/data/feeurnl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.